Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A navigation system for a host vehicle, the system comprising: at least one processing device programmed to: identify a navigational state associated with the host vehicle; determine a first predefined navigational constraint implicated by at least one aspect of the navigational state; identify a presence of at least one navigational constraint augmentation factor; determine a second navigational constraint based on identification of the at least one navigational constraint augmentation factor, wherein the second navigational constraint is different from the first navigational constraint and includes at least one characteristic augmented with respect to the first navigational constraint; determine, based on the identified navigational state, a navigational action for the host vehicle satisfying the second navigational constraint; and cause at least one adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.
The navigation system for a host vehicle dynamically adjusts navigation constraints based on real-time conditions to improve safety and efficiency. The system identifies the current navigational state of the vehicle, such as its position, speed, and surrounding environment. It then determines an initial navigational constraint, which could be a speed limit, lane-keeping requirement, or other operational limit derived from the vehicle's state. The system further detects augmentation factors—external or internal conditions that modify the initial constraint. These factors may include weather, traffic, vehicle performance, or driver behavior. Based on these factors, the system adjusts the initial constraint to a second, more stringent or relaxed constraint, ensuring it remains relevant to the current situation. For example, a speed limit may be reduced in heavy rain or increased on an empty highway. The system then calculates a navigational action, such as steering, braking, or acceleration, that complies with the adjusted constraint. Finally, it activates the vehicle's actuators to execute the action, ensuring safe and efficient navigation. This adaptive approach enhances vehicle responsiveness to changing conditions, reducing risks and optimizing performance.
2. The navigation system of claim 1 , wherein determination of the navigational action for the host vehicle satisfying the second navigational constraint occurs in a trained navigational system.
The invention relates to a navigation system for autonomous or semi-autonomous vehicles, addressing the challenge of determining optimal navigational actions while adhering to multiple constraints. The system is designed to process sensor data from the host vehicle and surrounding environment to identify potential navigational actions, such as lane changes, turns, or speed adjustments. A key feature is the ability to evaluate these actions against a first navigational constraint, which may include safety, traffic rules, or vehicle dynamics, and a second navigational constraint, which could involve user preferences, efficiency, or comfort. The system prioritizes actions that satisfy both constraints, ensuring safe and efficient navigation. A trained navigational system, likely a machine learning model, is used to determine the optimal action that meets the second constraint, leveraging historical data or learned patterns to make decisions. This approach improves decision-making accuracy and adaptability in dynamic driving scenarios. The system may also incorporate real-time updates from external sources, such as traffic signals or other vehicles, to refine its recommendations. The overall goal is to enhance autonomous driving capabilities by balancing safety, compliance, and user-specific requirements.
3. The navigation system of claim 1 , wherein the first predefined navigational constraint includes a first buffer zone associated with a detected object, wherein at least a portion of the first buffer zone extends a first distance from the detected object, and wherein the second navigational constraint includes a second buffer zone associated with the detected object, wherein at least a portion of the second buffer zone extends a second distance from the detected object greater than the first distance.
This invention relates to navigation systems designed to enhance safety and efficiency in autonomous or assisted driving by dynamically adjusting buffer zones around detected objects. The system addresses the problem of static buffer zones, which may either fail to provide sufficient safety margins or unnecessarily restrict vehicle movement. The invention introduces a navigation system that generates multiple buffer zones around detected objects, where each zone has a different distance from the object. The first buffer zone extends a shorter distance from the detected object, while the second buffer zone extends a longer distance. This dual-buffer approach allows the system to balance safety and maneuverability. For example, the first buffer zone may define a minimum safe distance for collision avoidance, while the second buffer zone may establish a broader safety margin for higher-speed or unpredictable scenarios. The system dynamically adjusts these buffer zones based on real-time data, such as object speed, trajectory, and environmental conditions, to optimize navigation paths. This adaptive buffering improves decision-making in autonomous vehicles by ensuring both safety and operational flexibility.
4. The navigation system of claim 1 , wherein the at least one navigational constraint augmentation factor includes a detected presence of snow or water on a road surface.
A navigation system is designed to improve route guidance by accounting for environmental conditions that affect road usability. The system detects and processes real-time data to identify navigational constraints, such as the presence of snow or water on road surfaces, which can impact vehicle safety and mobility. By integrating these constraints into route calculations, the system avoids or mitigates hazardous conditions, ensuring safer and more efficient travel. The system may use sensors, weather data, or user reports to detect these conditions and adjust navigation accordingly. This approach enhances traditional navigation by dynamically adapting to environmental factors that are not typically considered in static map-based routing. The goal is to provide drivers with optimized routes that minimize exposure to slippery or flooded roads, reducing accident risks and improving overall travel efficiency. The system may also prioritize alternative routes based on the severity of detected conditions, ensuring timely updates to navigation instructions. This adaptive functionality is particularly valuable in regions prone to rapid weather changes or seasonal road hazards.
5. The navigation system of claim 1 , wherein the at least one navigational constraint augmentation factor includes a detected decrease in image quality of a plurality of images representative of an environment of the host vehicle.
A navigation system for autonomous or semi-autonomous vehicles monitors environmental conditions to enhance navigation accuracy. The system detects a decrease in image quality from multiple images captured by onboard sensors, such as cameras, which represent the vehicle's surroundings. This degradation in image quality may result from factors like poor lighting, weather conditions, sensor obstructions, or sensor degradation. The system uses this detected decrease as a navigational constraint augmentation factor, meaning it adjusts navigation decisions to compensate for the reduced reliability of visual data. For example, the system may rely more heavily on alternative sensors like LiDAR or radar, reduce vehicle speed, or increase the frequency of sensor recalibration to maintain safe and accurate navigation. The system may also trigger alerts for the driver or autonomous control system to take corrective actions. This approach ensures that the vehicle adapts to changing environmental conditions, improving navigation robustness and safety. The system may integrate with other navigation components, such as mapping databases or localization algorithms, to provide a comprehensive solution for dynamic driving environments.
6. The navigation system of claim 1 , wherein the at least one navigational constraint augmentation factor includes detected particulates on an outer surface of a windshield of the host vehicle.
A navigation system for vehicles includes a method to enhance route guidance by incorporating real-time environmental factors that may affect visibility or driving conditions. The system detects particulates, such as dirt, dust, or debris, on the windshield of the host vehicle and uses this information to adjust navigation recommendations. For example, if the windshield is heavily obscured, the system may prioritize routes with fewer sharp turns or suggest stopping for cleaning. The system may also integrate other navigational constraint augmentation factors, such as weather conditions, road surface quality, or traffic congestion, to provide optimized route guidance. By dynamically assessing these factors, the system improves driver safety and efficiency by reducing visibility-related hazards and minimizing disruptions during travel. The navigation system processes sensor data from the vehicle, such as cameras or optical sensors, to detect windshield particulates and adjust navigation algorithms accordingly. This approach ensures that route planning accounts for real-world driving conditions, enhancing overall navigation accuracy and reliability.
7. The navigation system of claim 1 , wherein the at least one navigational constraint augmentation factor includes a detected failure of a least one sensor associated with the host vehicle.
A navigation system for autonomous or semi-autonomous vehicles includes a constraint augmentation module that dynamically adjusts navigational constraints based on real-time conditions. The system monitors sensor data from the host vehicle and surrounding environment to identify potential hazards or operational limitations. When a sensor failure is detected, the system modifies navigation constraints to ensure safe operation. For example, if a critical sensor like a LiDAR or radar unit fails, the system may reduce speed, increase following distance, or avoid complex maneuvers until the sensor is restored. The system also integrates other navigational constraint augmentation factors, such as weather conditions, traffic density, and road infrastructure, to optimize route planning and vehicle control. By continuously assessing sensor reliability and environmental factors, the system enhances safety and reliability in autonomous driving scenarios. The navigation system may also include predictive modeling to anticipate sensor failures or degradation, allowing proactive adjustments to constraints before issues arise. This adaptive approach ensures the vehicle operates within safe operational boundaries even under degraded sensor conditions.
8. The navigation system of claim 1 , wherein the navigational actuator includes at least one of a steering mechanism, a brake, or an accelerator.
A navigation system for autonomous vehicles addresses the challenge of precise control over vehicle movement to ensure safe and efficient navigation. The system includes a navigational actuator that interfaces with the vehicle's control mechanisms to execute navigation commands. This actuator comprises at least one of a steering mechanism, a brake, or an accelerator, enabling direct manipulation of the vehicle's direction, speed, and stopping power. The system also incorporates a navigation controller that processes sensor data, such as from cameras, LiDAR, or GPS, to determine the vehicle's position and surroundings. Based on this data, the controller generates navigation commands to guide the vehicle along a predetermined path or to avoid obstacles. The actuator then translates these commands into physical actions, such as turning the steering wheel, applying brakes, or adjusting acceleration. This integration ensures the vehicle responds accurately to real-time conditions, improving safety and navigation performance. The system may also include redundancy features, such as backup actuators or fail-safe mechanisms, to maintain control in case of component failure. By combining sensor-based decision-making with direct control over critical vehicle functions, the system enhances autonomous driving capabilities.
9. The navigation system of claim 1 , wherein that least one augmented characteristic includes an increased distance of at least a portion of a buffer zone associated with at least one of a pedestrian, a target vehicle, a detected object, or a roadside barrier.
This invention relates to navigation systems designed to enhance safety and situational awareness for autonomous or semi-autonomous vehicles. The system addresses the challenge of accurately detecting and responding to dynamic obstacles, such as pedestrians, other vehicles, or roadside barriers, to prevent collisions. The navigation system includes a buffer zone around these obstacles, which serves as a safety margin to ensure the vehicle maintains a safe distance. A key feature of the invention is the ability to dynamically adjust the buffer zone's distance based on real-time conditions. For example, the system can increase the buffer zone's size around a pedestrian, a target vehicle, a detected object, or a roadside barrier to provide additional safety clearance. This adjustment helps the vehicle avoid potential hazards more effectively, especially in unpredictable environments. The system may also incorporate additional augmented characteristics, such as modifying the buffer zone's shape or adjusting its boundaries based on sensor data or environmental factors. By dynamically adapting the buffer zone, the navigation system improves collision avoidance and overall safety for autonomous driving.
10. The navigation system of claim 1 , wherein the at least one augmented characteristic includes a decrease in speed associated with at least one predefined navigational constraint.
A navigation system is designed to enhance route guidance by incorporating augmented characteristics that modify navigation instructions based on real-world constraints. The system identifies predefined navigational constraints, such as speed limits, traffic conditions, or road hazards, and adjusts navigation guidance accordingly. Specifically, the system includes a feature that reduces the recommended speed when approaching or navigating through these constraints to improve safety and compliance. The navigation system may also provide alternative routes or dynamic rerouting to avoid areas with significant constraints. By dynamically adjusting speed recommendations and route guidance, the system ensures smoother, safer, and more efficient navigation for users. The augmented characteristics are derived from real-time data, historical traffic patterns, or predefined rules, allowing the system to adapt to varying conditions. This approach helps drivers or vehicle operators adhere to regulations, avoid potential hazards, and optimize travel time while maintaining safety. The system may be integrated into vehicle onboard computers, mobile devices, or standalone navigation units, providing flexible and context-aware navigation assistance.
11. The navigation system of claim 1 , wherein the at least one augmented characteristic includes a decrease in maximum allowable deceleration associated with at least one predefined navigational constraint.
This invention relates to navigation systems designed to improve vehicle safety and efficiency by dynamically adjusting navigational constraints based on real-time conditions. The system addresses the problem of fixed navigational constraints that do not account for varying road conditions, vehicle capabilities, or environmental factors, which can lead to unsafe or inefficient driving behaviors. The navigation system includes a processor configured to determine at least one augmented characteristic for a vehicle's navigation path. This augmented characteristic modifies predefined navigational constraints, such as speed limits or route guidance, to better align with current conditions. Specifically, the system can reduce the maximum allowable deceleration for a vehicle when approaching a predefined navigational constraint, such as a sharp turn, steep grade, or low-visibility area. This adjustment helps prevent abrupt braking, which can cause accidents or discomfort for passengers. The system may also incorporate data from sensors, vehicle telemetry, or external sources to assess road conditions, weather, traffic, or vehicle performance. By dynamically adjusting constraints, the navigation system enhances safety by ensuring that the vehicle operates within safer limits while maintaining efficient routing. The invention is particularly useful for autonomous or semi-autonomous vehicles, where precise control over deceleration and adherence to navigational constraints is critical.
12. An autonomous vehicle, the autonomous vehicle comprising: a frame; a body attached to the frame; and at least one processing device programmed to: identify a navigational state associated with the autonomous vehicle; determine a first predefined navigational constraint implicated by at least one aspect of the navigational state; identify a presence of at least one navigational constraint augmentation factor; determine a second navigational constraint based on identification of the at least one navigational constraint augmentation factor, wherein the second navigational constraint is different from the first navigational constraint and includes at least one characteristic augmented with respect to the first navigational constraint; determine, based on the identified navigational state, a navigational action for the autonomous vehicle satisfying the second navigational constraint; and cause at least one adjustment of a navigational actuator of the autonomous vehicle in response to the determined navigational action.
Autonomous vehicles operate in dynamic environments where navigation must adapt to real-time conditions. A key challenge is ensuring safe and efficient movement while adhering to constraints like speed limits, traffic rules, or environmental factors. This invention addresses this by dynamically adjusting navigational constraints based on real-time conditions to optimize vehicle behavior. The system includes a vehicle frame, body, and processing device that monitors the vehicle's navigational state, such as position, speed, or surrounding obstacles. It identifies a predefined navigational constraint (e.g., a speed limit) but also detects augmentation factors (e.g., weather, road conditions, or traffic density) that may require stricter or relaxed constraints. The system then adjusts the constraint (e.g., reducing speed in rain) and determines a navigational action (e.g., braking or steering) that complies with the updated constraint. Finally, it actuates the vehicle's control systems (e.g., brakes, steering) to execute the action. This approach improves safety and efficiency by dynamically adapting constraints rather than relying on static rules, allowing the vehicle to respond to unpredictable conditions while maintaining compliance with operational limits.
13. The autonomous vehicle of claim 12 , wherein determination of the navigational action for the autonomous vehicle satisfying the second navigational constraint occurs in a trained navigational system.
Autonomous vehicles require advanced navigation systems to safely and efficiently traverse complex environments while adhering to various constraints, such as traffic rules, obstacle avoidance, and passenger comfort. A key challenge is dynamically determining navigational actions that satisfy multiple conflicting constraints, such as minimizing travel time while ensuring safety. This invention addresses this problem by integrating a trained navigational system into an autonomous vehicle. The trained navigational system is designed to evaluate and select navigational actions that meet a second navigational constraint, which may include factors like energy efficiency, route optimization, or adherence to traffic regulations. The system leverages machine learning or other AI techniques to process sensor data, map information, and real-time environmental inputs to generate optimal navigation decisions. By using a trained model, the system can adapt to varying conditions and improve performance over time. This approach enhances the vehicle's ability to balance competing priorities, ensuring safe and efficient operation in diverse scenarios. The trained navigational system may be part of a broader autonomous driving framework that includes perception, planning, and control modules, working together to execute the determined actions. This solution improves upon traditional rule-based systems by incorporating learned behaviors and predictive capabilities, leading to more robust and flexible navigation.
14. The autonomous vehicle of claim 12 , wherein the first predefined navigational constraint includes a first buffer zone associated with a detected object, wherein at least a portion of the first buffer zone extends a first distance from the detected object, and wherein the second navigational constraint includes a second buffer zone associated with the detected object, wherein at least a portion of the second buffer zone extends a second distance from the detected object greater than the first distance.
Autonomous vehicles navigate environments by detecting and avoiding obstacles to ensure safe operation. A key challenge is determining appropriate buffer zones around detected objects to prevent collisions while allowing efficient movement. Existing systems often use fixed buffer zones, which may either be too restrictive, limiting vehicle maneuverability, or too permissive, increasing collision risks. This invention improves upon prior systems by dynamically adjusting buffer zones around detected objects based on contextual factors. The autonomous vehicle detects an object and establishes a first buffer zone extending a first distance from the object. This initial buffer zone defines a primary navigational constraint, ensuring the vehicle maintains a safe minimum distance. Additionally, a second buffer zone is created around the same object, extending a second distance greater than the first. This secondary buffer zone serves as an enhanced navigational constraint, providing an additional safety margin or operational flexibility depending on the situation. The vehicle's navigation system uses these buffer zones to plan trajectories that avoid collisions while optimizing path efficiency. The dynamic adjustment of buffer distances allows the vehicle to adapt to varying environmental conditions, such as object type, movement, or environmental hazards, improving both safety and performance.
15. The autonomous vehicle of claim 12 , wherein the at least one navigational constraint augmentation factor includes a detected presence of snow or water on a road surface.
Autonomous vehicles rely on navigation systems to safely traverse roadways, but adverse weather conditions like snow or water accumulation can degrade sensor performance and reduce traction, increasing collision risks. Existing systems may lack real-time detection of such hazards, leading to inadequate adjustments in vehicle behavior. This invention improves autonomous vehicle safety by incorporating navigational constraint augmentation factors, specifically detecting the presence of snow or water on road surfaces. The vehicle uses sensors, such as cameras, LiDAR, or radar, to identify these conditions. Upon detection, the system adjusts navigation parameters, such as speed, braking distance, or steering responsiveness, to mitigate risks. The vehicle may also communicate detected hazards to other vehicles or infrastructure to enhance collective safety. The system integrates with the vehicle's perception and decision-making modules, ensuring timely responses to dynamic road conditions. By dynamically adjusting navigation constraints based on real-time environmental data, the invention enhances autonomous vehicle reliability in adverse weather, reducing accidents and improving passenger safety. The solution is particularly valuable in regions prone to snow or flooding, where traditional navigation systems may fail to account for reduced friction or obscured road markings.
16. The autonomous vehicle of claim 12 , wherein the at least one navigational constraint augmentation factor includes a detected decrease in image quality of a plurality of images representative of an environment of the host vehicle.
Autonomous vehicles rely on sensor data, including images, to navigate and make decisions. However, environmental factors such as weather, lighting conditions, or sensor degradation can degrade image quality, leading to inaccurate or unreliable data for navigation. This degradation can impair the vehicle's ability to detect obstacles, recognize road markings, or interpret surroundings, increasing the risk of navigation errors or safety hazards. To address this, an autonomous vehicle system includes a navigational constraint augmentation module that detects a decrease in image quality from multiple images of the vehicle's environment. When poor image quality is identified, the system adjusts navigation constraints, such as reducing speed, increasing following distance, or activating alternative sensors (e.g., LiDAR or radar) to compensate for the degraded visual data. The system may also trigger alerts for the vehicle's operator or request human intervention if necessary. By dynamically adapting to image quality degradation, the vehicle maintains safer and more reliable operation in challenging conditions. This approach enhances situational awareness and reduces reliance on potentially unreliable visual inputs, improving overall navigation safety.
17. The autonomous vehicle of claim 12 , wherein the at least one navigational constraint augmentation factor includes detected particulates on an outer surface of a windshield of the autonomous vehicle.
Autonomous vehicles rely on sensors and cameras for navigation, but environmental factors like particulate buildup on windshields can degrade sensor performance and reduce visibility. This invention addresses the problem by incorporating detected particulates on the windshield as a navigational constraint augmentation factor in autonomous vehicle systems. The vehicle includes sensors to detect particulate accumulation on the windshield, which can obstruct camera or LiDAR sensors critical for perception and navigation. When particulates are detected, the system adjusts navigation parameters, such as reducing speed, increasing sensor redundancy, or triggering cleaning mechanisms to maintain safe operation. The vehicle may also use predictive models to anticipate particulate accumulation based on environmental conditions, such as dusty roads or inclement weather, and preemptively adjust navigation strategies. This approach ensures that the vehicle adapts to real-time environmental challenges, improving safety and reliability in autonomous driving. The system integrates with existing sensor networks and control algorithms to provide a comprehensive solution for maintaining optimal sensor performance under adverse conditions.
18. The autonomous vehicle of claim 12 , wherein the at least one navigational constraint augmentation factor includes a detected failure of a least one sensor associated with the autonomous vehicle.
Autonomous vehicles rely on sensor data for navigation, but sensor failures can degrade performance or cause unsafe conditions. This invention addresses the problem by augmenting navigational constraints in response to detected sensor failures. The autonomous vehicle includes a navigation system that monitors sensor health and dynamically adjusts operational parameters when a failure is detected. If a critical sensor, such as a LiDAR, camera, or radar unit, malfunctions, the system modifies the vehicle's path planning, speed, or other control inputs to maintain safety. The augmentation may involve rerouting to avoid high-risk areas, reducing speed, or activating redundant sensors. The system may also log the failure for diagnostics and future maintenance. This approach ensures continued safe operation despite partial sensor degradation, improving reliability in autonomous driving. The invention applies to any autonomous vehicle with sensor-based navigation, including self-driving cars, drones, and robotic systems.
19. The autonomous vehicle of claim 12 , wherein the navigational actuator includes at least one of a steering mechanism, a brake, or an accelerator.
Autonomous vehicles require precise control systems to navigate safely and efficiently. A key challenge is ensuring the vehicle can respond to dynamic environments by adjusting steering, braking, and acceleration. This invention addresses this by incorporating a navigational actuator system that includes at least one of a steering mechanism, a brake, or an accelerator. The actuator system enables the vehicle to execute precise maneuvers, such as turning, stopping, or accelerating, based on real-time sensor data and navigation algorithms. The steering mechanism allows for directional control, the brake ensures safe deceleration, and the accelerator manages speed adjustments. By integrating these components, the vehicle can autonomously navigate complex environments while maintaining safety and efficiency. The system may also include redundancy or fail-safe mechanisms to handle component failures, ensuring reliable operation. This approach enhances the vehicle's ability to adapt to varying road conditions, traffic scenarios, and emergency situations, improving overall autonomous driving performance.
20. The autonomous vehicle of claim 12 , wherein that least one augmented characteristic includes an increased distance of at least a portion of a buffer zone associated with at least one of a pedestrian, a target vehicle, a detected object, or a roadside barrier.
This invention relates to autonomous vehicle systems designed to enhance safety by dynamically adjusting buffer zones around pedestrians, vehicles, detected objects, or roadside barriers. The system improves collision avoidance by increasing the distance of at least a portion of the buffer zone surrounding these elements. This adjustment ensures the autonomous vehicle maintains a safer operating space, reducing the risk of accidents in dynamic environments. The buffer zone expansion can be applied selectively to specific areas or objects, allowing the vehicle to adapt to varying traffic conditions, pedestrian movements, or roadside hazards. The system may also integrate sensor data to detect and classify objects, determining the appropriate buffer zone adjustments based on factors such as object type, speed, or proximity. By dynamically modifying these safety margins, the autonomous vehicle can navigate more effectively in complex scenarios, such as crowded urban areas or construction zones, while maintaining compliance with safety regulations. The invention aims to address the challenge of unpredictable obstacles in autonomous driving by providing a flexible and responsive safety mechanism.
21. The autonomous vehicle of claim 12 , wherein the at least one augmented characteristic includes a decrease in speed associated with at least one predefined navigational constraint.
Autonomous vehicles are designed to navigate environments while adhering to safety and operational constraints. A key challenge is dynamically adjusting vehicle behavior to comply with predefined navigational constraints, such as speed limits, traffic rules, or environmental conditions, without compromising efficiency or passenger comfort. This invention relates to an autonomous vehicle equipped with systems to modify its operational characteristics in response to navigational constraints. The vehicle includes sensors and processing units to detect and interpret constraints, such as speed limits or road conditions, and adjust its behavior accordingly. Specifically, the vehicle can autonomously reduce its speed when encountering predefined constraints, ensuring compliance with regulations or safety protocols. The system may also integrate with mapping and traffic data to anticipate constraints and preemptively adjust speed or route planning. This approach enhances safety, regulatory compliance, and adaptability in varying environments. The vehicle may further incorporate machine learning to refine constraint responses based on historical data, improving long-term performance. The invention ensures that the vehicle operates within legal and operational boundaries while maintaining optimal navigation efficiency.
22. The autonomous vehicle of claim 12 , wherein the at least one augmented characteristic includes a decrease in maximum allowable deceleration associated with at least one predefined navigational constraint.
Autonomous vehicles are designed to navigate complex environments while ensuring passenger safety and comfort. A key challenge is balancing performance with adherence to navigational constraints, such as speed limits, road conditions, or traffic regulations. Existing systems may apply rigid deceleration limits, which can lead to inefficient braking or discomfort for passengers. This invention addresses the problem by modifying the vehicle's deceleration behavior based on predefined navigational constraints. The autonomous vehicle includes a control system that adjusts the maximum allowable deceleration in response to specific conditions, such as approaching a sharp curve, entering a school zone, or encountering slippery road surfaces. By dynamically reducing the maximum deceleration, the system ensures smoother braking, improved stability, and compliance with safety regulations. The adjustment can be based on real-time sensor data, map information, or predefined rules. This approach enhances passenger comfort, reduces wear on braking components, and minimizes the risk of skidding or loss of control. The invention is particularly useful in scenarios where sudden or aggressive braking could compromise safety or violate traffic laws.
23. A method of navigating an autonomous vehicle, the method comprising: identifying a navigational state associated with the autonomous vehicle; determining a first predefined navigational constraint implicated by at least one aspect of the navigational state; identifying a presence of at least one navigational constraint augmentation factor; determining a second navigational constraint based on identification of the at least one navigational constraint augmentation factor, wherein the second navigational constraint is different from the first navigational constraint and includes at least one characteristic augmented with respect to the first navigational constraint; determining, based on the identified navigational state, a navigational action for the autonomous vehicle satisfying the second navigational constraint; and causing at least one adjustment of a navigational actuator of the autonomous vehicle in response to the determined navigational action.
Autonomous vehicle navigation systems must adapt to dynamic environments while ensuring safety and efficiency. A method for navigating an autonomous vehicle addresses this by dynamically adjusting navigational constraints based on real-time conditions. The method first identifies the vehicle's current navigational state, such as its position, speed, or surrounding obstacles. It then determines a baseline navigational constraint derived from this state, which could include speed limits, lane boundaries, or collision avoidance thresholds. The system further detects the presence of augmentation factors—external or internal conditions that modify these constraints. For example, adverse weather, road conditions, or vehicle sensor limitations may require stricter constraints than initially defined. Based on these factors, the system recalculates a second, more stringent navigational constraint that augments the original one. The method then selects a navigational action that complies with this updated constraint, such as reducing speed or altering trajectory. Finally, the system adjusts the vehicle's actuators—steering, braking, or acceleration systems—to execute the action. This approach ensures the vehicle adapts proactively to changing conditions, enhancing safety and operational reliability.
Unknown
May 12, 2020
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